Cooperative Computing Group

The goal of the Cooperative Computing Group (CCG) is to research emerging Information Technologies and advances in Computer Science to support System-Level Science - the broad understanding of how complex, multiphenomena physical systems behave and how their constituent components interacts and interrelate. System-level Science integrates not only different disciplines vut also, typically, software systems, data, computing resources and people. System-level science is usually a team pursuit. Data comes from different sources, different groups develop component models, team members provide specialized expertise, and the often substantial computing and data resources required for success are themsevles diverse and distributed.

The use of distributed and often high-performance computing facilities for the solution of compute-intesive science and engineering problems is usually referred to as e-Science. The e-Science builds on two classes of technologies: Grid Computing and Web 2.0. Grid Computing is a collection of technologies which enable amassing geographically distributed resources (hardware, software, data) into shared virtual super-systems allowing autonomous execution of complex tasks and computational workflows on demand. In particular, Grid Computing supports the creation of virtual organizations for secure collaboration of researchers across administrative boundaries. Web 2.0 technologies complement Grid Computing by providing the infrastructure for creating rich web-based user interfaces and enhance collaborative environments to enable gathering collective intelligence, creating platforms for dissemination, sharing, and exchange of information, and encouraging broad particstyle="font-family:sans-serif;"ipation in research projects.

The mixture of Grid and Web technologies provides tools for Cooperative Computing - the environment for advancing system-level science. The CCG group, led by Dr. Tomasz Haupt, is applying the cooperative computing concepts to solve real-life complex problems such as Computational Material Enginieering (DOE, NSF), Mulilevel Design Optimizations (NSF), Rapid prototyping for Research of Sun-Earth System (NASA), Earthquake Engineering (NSF), Quantitative Human Physiology (NSF, NASA), Simulation Environment for Onboard Fire and Smoke Propagation (NRL) and All-Electric Ship Design (ONR).

Computational Material Design Design Optimizations Rapid Prototyping Earthquake Engineering Quantitative Human Physiology Fire and Smoke Propagation Electric Ship